There are two aims of audio file recognition: recognition of pieces of audio recordings, and matching of complete audio tracks.
Recognition technology is used for identifying of an audio recording by usage of a relatively short but potentially corrupted and noisy fragment of the audio track. A representative example is Shazam, which is a commercial smartphone-based music recognition service. Shazam uses a smartphone's built-in microphone to gather a brief sample of music being played. It creates an audio fingerprint based on the sample, and compares it against a database. Once the recognition is made, there is no need for any further processing, such as additional comparison of the matched file found in the database. Therefore, when a user is listening to a mix of melodies and tries to identify the melody, Shazam would identify the name of the actually playing piece of music.
Matching technology is aimed for the search of duplicates. Therefore, the duplicate of a mix of compositions would be the same mix of the same compositions. However, audio tracks can be deemed being duplicates when the difference between them consists in a slight duration difference, in a slight time shift, or in quality.
Since matching technology is aimed for the search of duplicates, comparison of larger portions of audio fingerprints is necessary. Comparison of larger portions of audio fingerprints is computer resource consuming (such as processing power, etc.).